No. 4 (2021)
Published:
2021-12-30
ARTICLES FROM THIS ISSUE
-
Performance Evaluation of MC-CDMA Systems with Single User Detection Technique using Kernel and Linear Adaptive Method
Abstract
Among all the techniques combining multi-carrier modulation and spread spectrum, the multi-carrier code division multiple access (MC-CDMA) system is by far the most widely studied. In this paper, we present the performance of the MC-CDMA system associated with key single-user detection techniques. We are interested in problems related to identification and equalization of mobile radio channels, using the kernel method in Hilbert space with a reproducing kernel, and a linear adaptive algorithm, for MC-CDMA systems. In this context, we tested the efficiency of these algorithms, considering practical frequency selective fading channels, called broadband radio access network (BRAN), standardized for MC-CDMA systems. As far as the equalization problem encountered after channel identification is concerned, we use the orthogonality restoration combination (ORC) and the minimum mean square error (MMSE) equalizer techniques to correct the distortion of the channel. Simulation results demonstrate that the kernel algorithm is efficient for practical channels
-
Phonetic Segmentation using a Wavelet-based Speech Cepstral Features and Sparse Representation Classifier
Abstract
Speech segmentation is the process of dividing speech signal into distinct acoustic blocks that could be words, syllables or phonemes. Phonetic segmentation is about finding the exact boundaries for the different phonemes that composes a specific speech signal. This problem is crucial for many applications, i.e. automatic speech recognition (ASR). In this paper we propose a new model-based text independent phonetic segmentation method based on wavelet packet speech parametrization features and using the sparse representation classifier (SRC). Experiments were performed on two datasets, the first is an English one derived from TIMIT corpus, while the second is an Arabic one derived from the Arabic speech corpus. Results showed that the proposed wavelet packet decomposition features outperform the MFCC features in speech segmentation task, in terms of both F1-score and R-measure on both datasets. Results also indicate that the SRC gives higher hit rate than the famous k-Nearest Neighbors (k-NN) classifier on TIMIT dataset
-
Research Concerning Electromagnetic Emissions from Residential On-grid PV Systems
Abstract
The paper presents the results of grid power quality tests and wide frequency electromagnetic radiation level tests to which home power networks with photovoltaic systems have been subjected. The said results are meaningful from the point of view of safety and compatibility of electrical devices and the power supply system they are connected to. The tests covered stability of phase voltage and its frequency, harmonic level flicker, as well as RF radiated and emission levels. The measurements performed provide an answer to the question concerning the level of compliance of randomly selected home-installed PV systems with applicable recommendations and regulations concerning electromagnetic compatibility. The ability to meet the applicable standards translates into the health and safety of building inhabitants, which is the ultimate goal. Legal regulations concerning electromagnetic compatibility of renewable energy sources are consistent throughout the entire European Union
-
Impact of Structures on the Operation of Air Traffic Radiolocation and Radionavigation Surveillance Systems
Abstract
The article describes interference affecting the operation of radiolocation and radionavigation devices used in the air traffic surveillance systems, caused by the proximity of building structures. The impact of a hypothetical structure on the operation of primary and secondary air traffic surveillance radars and DVOR/DME beacons was simulated. The results of this simulation are presented in the form of airspace sectors in which false identification of aircraft may occur, and where it will not be possible to identify aircraft or use beacons due to the certain portion of airspace being in the shadow created by the structure. Analysis of the possibility of the PSR radar receiver being blocked by a strong signal reflected from a nearby building was performed as well
-
Accurate Location of Fiber Cable Fault with OTDR
Abstract
The paper reviews the factors limiting the accuracy of locating a fiber optic cable fault when using an optical time domain reflectometer (OTDR) and describes an error estimation method for typical use cases. The primary source of errors lies in the complex relationship between the length of the optical fiber (measured by OTDR), its routing, cable design depending on cable design and type of installation (i.e. duct, directly buried, aerial) as well as the spare lengths used for service purposes. The techniques which considerably improve the accuracy of the fault localization processes are presented, the importance of accurate documentation of the network and of referencing the fault location to the nearest splice instead of end of the line are discussed, as is the absence of cable helix factor in data sheets
-
Fusion of Depth and Thermal Imaging for People Detection
Abstract
The methodology presented in this paper covers the topic of automatic detection of humans based on two types of images that do not rely on the visible light spectrum, namely on thermal and depth images. Various scenarios are considered with the use of deep neural networks being extensions of Faster R-CNN models. Apart from detecting people, independently, with the use of depth and thermal images, we proposed two data fusion methods. The first approach is the early fusion method with a 2-channel compound input. As it turned out, its performance surpassed that of all other methods tested. However, this approach requires that the model be trained on a dataset containing both types of spatially and temporally synchronized imaging sources. If such a training environment cannot be setup or if the specified dataset is not sufficiently large, we recommend the late fusion scenario, i.e. the other approach explored in this paper. Late fusion models can be trained with single-source data. We introduce the dual-NMS method for fusing the depth and thermal imaging approaches, as its results are better than those achieved by the common NMS
-
Has the Internet Saved the Economy? Modeling Impact of ICT Sector and COVID-19 on GDP
Abstract
This paper presents the influence of the COVID19 pandemic on gross domestic product (GDP) per capita for the 27 countries of the European Union. A panel model with fixed effects was applied to a dataset from 2010 to 2020. The analysis covered 13 independent variables, including nine related to the telecommunications market, and assessed their impact on GDP per capita. A variable related to the number of COVID-19 deaths per one thousand inhabitants was then added to the model. The results showed that COVID-19 is a significant factor and is negatively correlated with GDP per capita. The analysis described in the article has also shown that the importance of the ICT sector increased during the pandemic, i.e. the household broadband Internet variable became statistically significant
